Beam hopping resource allocation method taking user service weight gain as objective function

Abstract

The invention discloses a hopping beam resource allocation method taking a user service weight gain as a target function. The method comprises the following steps: calculating the service volume and time delay tolerance of each cell at the current time slot; establishing an optimization problem based on a decision problem with maximization of the deviation by taking the maximum total deviation of all attributes to the decision scheme as a target; solving the optimization problem, and determining an optimal attribute pair decision scheme; and performing resource allocation on each cell according to the optimal attribute decision scheme, and completing hopping beam resource allocation taking the user service weight gain as a target function. The method can meet real-time business service requirements and improve the overall throughput of the system.

Description

technical field [0001] The invention belongs to the field of beam-hopping satellite systems, and relates to a beam-hopping resource allocation method with user service weight gain as an objective function. Background technique [0002] With the development of broadband satellite communications, the demand for large capacity, high speed, and wide coverage has increased significantly. Most of the current wide satellite systems use multi-spot beams to increase system capacity. This system uses a fixed method to allocate resources. The power and frequency resources allocated to each beam are fixed, accounting for only a small part of the total on-board resources. Due to the diversity of service types, spatial inhomogeneity and time-varying service distribution, the way of fixed allocation of resources cannot meet the requirements of efficient transmission and on-demand coverage, resulting in waste of communication resources. [0003] In order to effectively use the resources on...

AI Technical Summary

Problems solved by technology

Different services have different transmission delay requirements. If we continue to use the traditional beam-hopping resource allocation algorithm and pursue the maximum system capacity for users in each time slot, then real-time services require high transmission delay due to the small number of requests, and packet loss will occur. Second, due to the high tolerance of non-real-time services to transmission delay, services can be stored for a period of time before transmission to achieve the maximum utilization of resources, while the traditional beam-hopping algorithm pursues the user with the largest number of service requests in each time slot. For transmission, when the amount of resources that can be provided by beam hopping is large, it will cause excess transmission resources, which will lead to waste of beam hopping resources and reduce the overall throughput of the system

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